Now that you've got a good sense of how to 'speak' R, let's use it with linear regression to make distinctive predictions.

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

When multiple variables are associated with a response, the interpretation of a prediction equation is seldom simple.

The literature of regression analysis with missing values of the independent variables is reviewed. Six classes of procedures are distinguished: complete case analysis, available case methods, least ...

Multiple regression models with survey data Regression becomes a more useful tool when researchers want to look at multiple factors simultaneously. If we want to know whether the racial divide ...

Conclusions: Generalised linear models are attractive for the regression of cost data because they provide parametric methods of analysis where a variety of non-normal distributions can be specified ...